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    Home / Central Data Catalog / MWI_2010-2019_IHPS_V06_M / variable [F389]
central

Integrated Household Panel Survey 2010-2013-2016-2019 (Long-Term Panel, 102 EAs)

Malawi, 2010 - 2019
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Reference ID
MWI_2010-2019_IHPS_v06_M
Producer(s)
National Statistical Office (NSO)
Metadata
DDI/XML JSON
Created on
Jan 16, 2021
Last modified
Jul 19, 2023
Page views
404370
Downloads
3120
  • Study Description
  • Data Dictionary
  • Downloads
  • Get Microdata
  • Data files
  • HouseholdGeovariables_IHS3_Rerelease_10
  • PlotGeovariables_IHS3_Rerelease_10
  • hh_mod_a_filt_10
  • hh_mod_b_10
  • hh_mod_c_10
  • hh_mod_d_10
  • hh_mod_e_10
  • hh_mod_f_10
  • hh_mod_g1_10
  • hh_mod_g2_10
  • hh_mod_g3_10
  • hh_mod_h_10
  • hh_mod_i1_10
  • hh_mod_i2_10
  • hh_mod_j_10
  • hh_mod_k_10
  • hh_mod_l_10
  • hh_mod_m_10
  • hh_mod_n1_10
  • hh_mod_n2_10
  • hh_mod_o_10
  • hh_mod_p_10
  • hh_mod_q_10
  • hh_mod_r_10
  • hh_mod_s1_10
  • hh_mod_s2_10
  • hh_mod_t_10
  • hh_mod_u_10
  • hh_mod_v_10
  • hh_mod_w_10
  • hh_mod_x_10
  • ag_mod_a_filt_10
  • ag_mod_b_10
  • ag_mod_c_10
  • ag_mod_d_10
  • ag_mod_e_10
  • ag_mod_f_10
  • ag_mod_g_10
  • ag_mod_h_10
  • ag_mod_i_10
  • ag_mod_j_10
  • ag_mod_k_10
  • ag_mod_l_10
  • ag_mod_m_10
  • ag_mod_n_10
  • ag_mod_o_10
  • ag_mod_p_10
  • ag_mod_q_10
  • ag_mod_r1_10
  • ag_mod_r2_10
  • ag_mod_s_10
  • ag_mod_t1_10
  • ag_mod_t2_10
  • ag_network_10
  • fs_mod_b_filt_10
  • fs_mod_c_10
  • fs_mod_d1_10
  • fs_mod_d2_10
  • fs_mod_d3_10
  • fs_mod_e1_10
  • fs_mod_e2_10
  • fs_mod_f1_10
  • fs_mod_f2_10
  • fs_mod_g_10
  • fs_mod_h1_10
  • fs_mod_h2_10
  • fs_mod_h3_10
  • fs_mod_i1_10
  • fs_mod_i2_10
  • fs_mod_j1_10
  • fs_mod_j2_10
  • com_ca_10
  • com_cb_10
  • com_cc_10
  • com_cd_10
  • com_ce_10
  • com_cf_10
  • com_cg1_10
  • com_cg2_10
  • com_ch_10
  • com_ci_10
  • com_cj_10
  • com_ck_10
  • HouseholdGeovariables_IHPS_13
  • PlotGeovariables_IHPS_13
  • hh_meta_13
  • hh_mod_a_filt_13
  • hh_mod_b_13
  • hh_mod_c_13
  • hh_mod_d_13
  • hh_mod_e_13
  • hh_mod_f_13
  • hh_mod_g1_13
  • hh_mod_g2_13
  • hh_mod_g3_13
  • hh_mod_h_13
  • hh_mod_i1_13
  • hh_mod_i2_13
  • hh_mod_j_13
  • hh_mod_k_13
  • hh_mod_l_13
  • hh_mod_m_13
  • hh_mod_n1_13
  • hh_mod_n2_13
  • hh_mod_o_13
  • hh_mod_p_13
  • hh_mod_q_13
  • hh_mod_r_13
  • hh_mod_s1_13
  • hh_mod_s2_13
  • hh_mod_t_13
  • hh_mod_u_13
  • hh_mod_v_13
  • hh_mod_x_13
  • ag_meta_13
  • ag_mod_b1_13
  • ag_mod_ba_13
  • ag_mod_bb_13
  • ag_mod_c_13
  • ag_mod_d_13
  • ag_mod_e1_13
  • ag_mod_e2_13
  • ag_mod_e3_13
  • ag_mod_e4_13
  • ag_mod_e5_13
  • ag_mod_f_13
  • ag_mod_g_13
  • ag_mod_h_13
  • ag_mod_i_13
  • ag_mod_i1_13
  • ag_mod_j_13
  • ag_mod_k_13
  • ag_mod_l_13
  • ag_mod_m_13
  • ag_mod_n_13
  • ag_mod_nr_13
  • ag_mod_o_13
  • ag_mod_o1_13
  • ag_mod_o2_13
  • ag_mod_p_13
  • ag_mod_q_13
  • ag_mod_r1_13
  • ag_mod_r2_13
  • ag_mod_s_13
  • ag_mod_t1_13
  • ag_mod_t2_13
  • ag_mod_u1_13
  • ag_mod_u2_13
  • ag_mod_u3_13
  • ag_mod_u4_13
  • fs_meta_13
  • fs_mod_a_13
  • fs_mod_b_13
  • fs_mod_c_13
  • fs_mod_d1_13
  • fs_mod_d2_13
  • fs_mod_d3_13
  • fs_mod_d4_13
  • fs_mod_e1_13
  • fs_mod_e2_13
  • fs_mod_f1_13
  • fs_mod_f2_13
  • fs_mod_g_13
  • fs_mod_h1_13
  • fs_mod_h2_13
  • fs_mod_h3_13
  • fs_mod_h4_13
  • fs_mod_i1_13
  • fs_mod_i2_13
  • fs_mod_j1_13
  • fs_mod_j2_13
  • com_meta_13
  • com_mod_a_13
  • com_mod_b_13
  • com_mod_c_13
  • com_mod_d_13
  • com_mod_e_13
  • com_mod_f1_13
  • com_mod_f2_13
  • com_mod_g_13
  • com_mod_h_13
  • com_mod_i_13
  • com_mod_j_13
  • com_mod_k_13
  • hh_meta_16
  • hh_mod_c_16
  • hh_mod_d_16
  • hh_mod_e_16
  • hh_mod_f_16
  • hh_mod_g1_16
  • hh_mod_g2_16
  • hh_mod_g3_16
  • hh_mod_h_16
  • hh_mod_i1_16
  • hh_mod_i2_16
  • hh_mod_j_16
  • hh_mod_k1_16
  • hh_mod_k2_16
  • hh_mod_l_16
  • hh_mod_m_16
  • hh_mod_n1_16
  • hh_mod_n2_16
  • hh_mod_o_16
  • hh_mod_p_16
  • hh_mod_q_16
  • hh_mod_r_16
  • hh_mod_s1_16
  • hh_mod_s2_16
  • hh_mod_t_16
  • hh_mod_u_16
  • hh_mod_v_16
  • hh_mod_w_16
  • hh_mod_x_16
  • IHPS2016MemberDatabase_16
  • ag_meta_16
  • ag_mod_a_16
  • ag_mod_b1_16
  • ag_mod_b2_16
  • ag_mod_c_16
  • ag_mod_d_16
  • ag_mod_e1_16
  • ag_mod_e2_16
  • ag_mod_e3_16
  • ag_mod_e4_16
  • ag_mod_f_16
  • ag_mod_g_16
  • ag_mod_h_16
  • ag_mod_i_16
  • ag_mod_i1_16
  • ag_mod_i2_16
  • ag_mod_j_16
  • ag_mod_k_16
  • ag_mod_l_16
  • ag_mod_m_16
  • ag_mod_n_16
  • ag_mod_nr_16
  • ag_mod_o_16
  • ag_mod_o1_16
  • ag_mod_o2_16
  • ag_mod_p_16
  • ag_mod_q_16
  • ag_mod_r1_16
  • ag_mod_r2_16
  • ag_mod_s_16
  • ag_mod_t1_16
  • ag_mod_t2_16
  • ag_mod_u_16
  • ag_mod_v_16
  • PlotGeovariablesIHPSY3_16
  • fs_meta_16
  • fs_mod_a_16
  • fs_mod_b_16
  • fs_mod_c_16
  • fs_mod_d1_16
  • fs_mod_d2_16
  • fs_mod_d3_16
  • fs_mod_e1_16
  • fs_mod_e2_16
  • fs_mod_f1_16
  • fs_mod_f2_16
  • fs_mod_g_16
  • fs_mod_h1_16
  • fs_mod_h2_16
  • fs_mod_h3_16
  • fs_mod_i1_16
  • fs_mod_j1_16
  • fs_mod_j2_16
  • com_meta_16
  • com_ca_16
  • com_cb_16
  • com_cc_16
  • com_cd_16
  • com_ce_16
  • com_cf1_16
  • com_cf2_16
  • com_ch_16
  • com_ci_16
  • com_cj_16
  • HouseholdGeovariablesIHPSY3
  • hh_mod_b_16
  • com_mod_cg_16
  • IND_MOD_A
  • IND_MOD_B
  • IND_MOD_F
  • IND_MOD_H
  • IND_MOD_I
  • IND_MOD_J
  • IND_MOD_K
  • IND_MOD_L
  • IND_MOD_NR
  • IND_MOD_G
  • hh_meta_19
  • hh_mod_b_19
  • hh_mod_c_19
  • hh_mod_d_19
  • hh_mod_e_19
  • hh_mod_f_19
  • hh_mod_f1_19
  • hh_mod_g1_19
  • hh_mod_g2_19
  • hh_mod_g3_19
  • hh_mod_h_19
  • hh_mod_i1_19
  • hh_mod_i2_19
  • hh_mod_j_19
  • hh_mod_k1_19
  • hh_mod_k2_19
  • hh_mod_l_19
  • hh_mod_m_19
  • hh_mod_n1_19
  • hh_mod_n2_19
  • hh_mod_o_19
  • hh_mod_p_19
  • hh_mod_q_19
  • hh_mod_r_19
  • hh_mod_s1_19
  • hh_mod_s2_19
  • hh_mod_t_19
  • hh_mod_u_19
  • hh_mod_v_19
  • hh_mod_w_19
  • hh_mod_x_19
  • ihps2019memberdatabase
  • ag_meta_19
  • ag_mod_a_19
  • ag_mod_b2_19
  • ag_mod_c_19
  • ag_mod_d_19
  • ag_mod_e1_19
  • ag_mod_e2_19
  • ag_mod_e3_19
  • ag_mod_e4_19
  • ag_mod_f_19
  • ag_mod_g_19
  • ag_mod_h_19
  • ag_mod_i_1_19
  • ag_mod_i2_19
  • ag_mod_j_19
  • ag_mod_k_19
  • ag_mod_l_19
  • ag_mod_m_19
  • ag_mod_n_19
  • ag_mod_nr_19
  • ag_mod_o_1_19
  • ag_mod_o_19
  • ag_mod_o2_19
  • ag_mod_p_19
  • ag_mod_q_1_19
  • ag_mod_q_19
  • ag_mod_r1_19
  • ag_mod_r2_19
  • ag_mod_s_19
  • ag_mod_t1_19
  • ag_mod_t2_19
  • fs_meta_19
  • fs_mod_a_19
  • fs_mod_b_19
  • fs_mod_c_19
  • fs_mod_d1_19
  • fs_mod_d2_19
  • fs_mod_d3_19
  • fs_mod_e1_19
  • fs_mod_e2_19
  • fs_mod_f1_19
  • fs_mod_f2_19
  • fs_mod_g_19
  • fs_mod_h1_19
  • fs_mod_h2_19
  • fs_mod_h3_19
  • fs_mod_i1_19
  • fs_mod_i2_19
  • fs_mod_j1_19
  • fs_mod_j2_19
  • com_ca_19
  • com_cb_19
  • com_cc_19
  • com_cd_19
  • com_ce_19
  • com_cf1_19
  • com_cf2_19
  • com_cg_19
  • com_ch_19
  • com_ci_19
  • com_meta_19
  • com_cj_19
  • com_ck_19
  • ihs_foodconversion_factor_2020
  • caloric_conversionfactor
  • hh_mod_a_filt_16
  • hh_mod_a_filt_19
  • ihs_seasonalcropconversion_factor_2020
  • ihs_treeconversion_factor_2020
  • plotgeovariables_y4
  • householdgeovariables_y4

Description of Events (com_cg35b)

Data file: com_cg_19

Overview

Valid: 656
Invalid: 0
Type: Discrete
Start: 10
End: 90
Width: 81
Range: -
Format: character

Questions and instructions

Categories
Value Category Cases
1 Block Primary school 1
0.2%
2 new School Block 1
0.2%
ANIMAL DISEASES 1
0.2%
African rising teachers in agriculture 1
0.2%
Animal Diseases 1
0.2%
Army worm 1
0.2%
Armyworms 1
0.2%
BAD RAINS AND HEAVY WINDS 1
0.2%
BOREHOLE 1
0.2%
BOZI, ATTACK FARMERS CROPS 1
0.2%
BRIDGE CONSTRUCTION 1
0.2%
Bad roads 1
0.2%
Bank Mnkhonde 1
0.2%
Bed budds 1
0.2%
Borehole 2
0.3%
Boreholes 1
0.2%
Bridge Building 1
0.2%
Building of pharmacy,maternity wing and new and toilets 1
0.2%
Business not progressing - tax 1
0.2%
CBCC 1
0.2%
CBO 1
0.2%
CLIMATE CHANGE 1
0.2%
CONSTRUCTION OF BOREHOLE 1
0.2%
CONSTRUCTION OF BRIDGE 1
0.2%
CONSTRUCTION OF CITY LIGHTS 1
0.2%
CONSTRUCTION OF COMMUNAL TAP 1
0.2%
CONSTRUCTION OF COMMUNAL TAPS 1
0.2%
CONSTRUCTION OF COMMUNITY POLICE 1
0.2%
CONSTRUCTION OF KIOSKS 1
0.2%
CONSTRUCTION OF NEW ROAD 1
0.2%
CONSTRUCTION OF NEW SCHOOL BLOCK 1
0.2%
CONSTRUCTION OF ROAD 1
0.2%
CONSTRUCTION OF SCHOOL BLOCK 1
0.2%
CONSTRUCTION OF TWO BRIDGES. 1
0.2%
CONSTRUCTION SELF BOARDING SCHOOL BLOCK 1
0.2%
CONTRUCTION OF SCHOOL BLOCK 1
0.2%
CROP DISEASE 1
0.2%
CROP DISEASE (WORMS) 1
0.2%
CROP DISEASE(WORMS) 1
0.2%
CROP DISEASES 1
0.2%
CROP INSECTS 1
0.2%
CROP PESTS 2
0.3%
Cash transfer (mtukula pankhomo) 1
0.2%
Cholera 1
0.2%
Climate Charge 1
0.2%
Climate change ( un predictable rains) 1
0.2%
Construction of Junior primary school 1
0.2%
Construction of a school block 1
0.2%
Construction of aunderfive clinic 1
0.2%
Construction of new road 1
0.2%
Construction of one primary school teacher house 1
0.2%
Construction of school blocks 1
0.2%
Construction of water board kiosk 1
0.2%
Coupon 1
0.2%
Crop Pest 2
0.3%
Crop Pests 2
0.3%
Crop failure 4
0.6%
Crop pests 3
0.5%
Crop pests and disease 1
0.2%
Crop production 1
0.2%
Crops Diseases 2
0.3%
Crops affected by dieses 1
0.2%
DISTRIBUTION OF FREE MAIZE 1
0.2%
DISTRIBUTION OF NETS 1
0.2%
DISTRUCTION OF HOUSES DEW TO HIGH RAINFALL 1
0.2%
DROUGHT 3
0.5%
DROUGT 1
0.2%
DRY SPEL 3
0.5%
Demonstrations 1
0.2%
Destruction of DU due to rains 1
0.2%
Disease epidemic 1
0.2%
Donated spraying medicine to kill armyworms 1
0.2%
Drag abuse 1
0.2%
Drought 15
2.3%
Dry spell 1
0.2%
EMPLOYMENT OPPORTUNITIES 1
0.2%
EMPLOYMENT OPPORTUNITY FROM MASAF 1
0.2%
Electricity 4
0.6%
Electricity bills too much 1
0.2%
Epidermic animal disease in the area 1
0.2%
Erratic rains 3
0.5%
Events that made people better off 101
15.4%
Events that made people worse off 101
15.4%
Expensive Agriculture inputs 1
0.2%
Expensive of agriculture commodities like s bag of maize and fertilizer 1
0.2%
Expensive of farm implements eg fertilizer 1
0.2%
FALL ARMY WORM 1
0.2%
FISPI 1
0.2%
FOOD AID 1
0.2%
Farmers do not have chancy to give price on their oroduce 1
0.2%
Feeding programme 1
0.2%
Fertilizer subsidy 1
0.2%
Floating of songwe which washed away some crops 1
0.2%
Flood 5
0.8%
Flooding 1
0.2%
Flooding due to heavy rains 1
0.2%
Floods 13
2%
Focus 1
0.2%
Food Aid 1
0.2%
Food aids 1
0.2%
Food aids and mtukula pakhomo 1
0.2%
Food distribution programme 1
0.2%
Food too expensive 1
0.2%
Free Food from NGOs 1
0.2%
Free food 3
0.5%
Free food distribution 1
0.2%
Free maize 1
0.2%
Good Gravel roads 1
0.2%
Good harvest 1
0.2%
Good price of sweeetpotatoes 1
0.2%
HEALTY FACILITY 1
0.2%
HEAVY RAIN THAT DESTROY HOUSES 1
0.2%
HEAVY RAINFALL 2
0.3%
HEAVY RAINFALL THAT CAUSE LOTS OF DAMAGES TO MANY PEOPLE IN THIS COMMUNITY. 1
0.2%
HEAVY RAINFALL THAT CAUSE LOTS OF DAMAGES. 1
0.2%
HEAVY RAINFALL(IDAHI) 1
0.2%
HIGH COST OF FOOD ITEMS 1
0.2%
HIGH PRICE OF AGRICULTURAL ITEMS 1
0.2%
HIGH PRICE OF COMMODITIES 2
0.3%
HIGH PRICE OF FARM IMPREMENTS 1
0.2%
HIGH PRICE OF FARM IMPUTS 1
0.2%
HIGH PRICE OF FARM INPUTS 1
0.2%
HIGH PRICES OF FOOD 1
0.2%
Harsh wind 1
0.2%
Healthy clinic in the Community 1
0.2%
Heavy rains 1
0.2%
Heavy rainfall 1
0.2%
Heavy rains 5
0.8%
Heavy rains ( floods) 1
0.2%
Heavy winds 1
0.2%
High Price of agriculture inputs 1
0.2%
High price of agricultural inputs 1
0.2%
High price rate of inputs 1
0.2%
High prices of Agriculture inputs 1
0.2%
High prices of Maize 1
0.2%
High prices of imputs 1
0.2%
High prices of inputs 4
0.6%
High prices of inputs and maize 1
0.2%
Hospital construction 1
0.2%
Houses fall down 1
0.2%
Housing Rent too expensive 1
0.2%
Hunger 1
0.2%
INTRODUCTION OF CHROLINE DISPANCER 1
0.2%
INTRODUCTION OF ELECTRICITY 1
0.2%
INTRODUCTION OF NEW WATER SYSTEM LINE 1
0.2%
IRREGULAR RAINS 3
0.5%
IRRIGULAR RAINS 1
0.2%
KAPUCHI (ARMY WORMS) 1
0.2%
KAPUCHI EPDERMIC CROP DISEASE 1
0.2%
Kapuchi 1
0.2%
LACK OF EMPLOYMEMT OPPORTUNITIES 1
0.2%
LOSS OF EMPLOYMENT OPPORTUNITIES 1
0.2%
LOW PRICES OF FARM PRODUCE AT THE MARKET 1
0.2%
Lack of coupons 1
0.2%
Lack of fertilizer subsday 1
0.2%
Lack of food 1
0.2%
Land grabbing 1
0.2%
Livestock Deceases 1
0.2%
Livestock Disease 1
0.2%
Livestock diseases 2
0.3%
Loss of jobs 1
0.2%
Low price of agriculture products 1
0.2%
Low salaries 1
0.2%
Luck of capital to start business 1
0.2%
MAIZE CROP DISEASES 1
0.2%
MAIZE DISTRIBUTION TO THE VILLAGERS 1
0.2%
MASAF 4 1
0.2%
MASAF PROGRAM 1
0.2%
MASAF public works 1
0.2%
MTUKULA PANKHOmo 1
0.2%
Maize Sales 1
0.2%
Malaria 1
0.2%
Malata subcidy 1
0.2%
Manja Lends program 1
0.2%
Marep project ( electric project) 1
0.2%
Market is not available 1
0.2%
Masaf 1
0.2%
Masaf program 1
0.2%
Mbozi 1
0.2%
Mesip 1
0.2%
Mnjigo in the are 1
0.2%
Mntukula Pankhomo 1
0.2%
Mntukula pankhomo 1
0.2%
More than enough rains 1
0.2%
Mtukula Pakhomo 1
0.2%
Mtukula pakhomo 1
0.2%
Mtukula pankhomo 2
0.3%
Mtukula pankhomo (under Masaf 4) 1
0.2%
Natural Disasters 2
0.3%
Net distribution in the area 1
0.2%
New 2 School Blocks 1
0.2%
New Borehole 1
0.2%
New Employment opportunity 1
0.2%
New Road 1
0.2%
New School 1
0.2%
New Teacher's house 1
0.2%
New block school 1
0.2%
New employment 1
0.2%
New house for HSA 1
0.2%
New road 2
0.3%
New road construction 1
0.2%
No employment oportunities 1
0.2%
No market for Pegion peas 1
0.2%
No market for farm produce 1
0.2%
No market to sell their products 1
0.2%
Ntukula pakhomo 2
0.3%
Outbreak of crop worms 1
0.2%
PESTS AND DEASES TO CROPS 1
0.2%
PESTS AND DKSEASE THAT AFFECTED CROPS 1
0.2%
POOR TRANSPORT 1
0.2%
POWER OUTAGES 1
0.2%
POWEROTAGES 1
0.2%
POWEROUTAGES 2
0.3%
PRICE INCREASE OF INPUT 1
0.2%
Pest and dieases 1
0.2%
Pest and diseases 1
0.2%
Pest and diseases affects crops 1
0.2%
Pest disease 1
0.2%
Pests 1
0.2%
Pests and Disease epidemic 1
0.2%
Pests attack roots and leaves of maize crops ( stock bores) 1
0.2%
Pests disease 1
0.2%
Pharmancy 1
0.2%
Piped Water at Primary 1
0.2%
Political Instability 1
0.2%
Political instability 1
0.2%
Poor Roads Structures 1
0.2%
Power outage's 1
0.2%
Power outages 2
0.3%
Price Fluactions 1
0.2%
Price Fluctuations 2
0.3%
Price fluctuation of farm produce 1
0.2%
Price fluctuations 7
1.1%
Price increaese 1
0.2%
Primary School Shelter 1
0.2%
RECEIVED MAIZE 1
0.2%
RISE OF AGRICUITURE input 1
0.2%
ROAD MAINTANCE 1
0.2%
RURAL ELECTRIFICATION 1
0.2%
Reduced social benefits on agriculture inputs 1
0.2%
River flooding 1
0.2%
Road construction 1
0.2%
School block 1
0.2%
School fence 1
0.2%
School Block 1
0.2%
School Blocks 1
0.2%
School Feeding programme 1
0.2%
School feeding progtamme 1
0.2%
Selling food stuff 1
0.2%
Sharp prices of agricultural 1
0.2%
Shortage of water 1
0.2%
Shorteg of rain 1
0.2%
Skin disease 1
0.2%
Skin dsease 1
0.2%
Social safety nets (phones and cash) 1
0.2%
Stalk borers 1
0.2%
Stock (pests) ZIMBOZI 1
0.2%
Storm 1
0.2%
Strong wind 1
0.2%
Strong wind which destroy crops in the community 1
0.2%
THIEVES IN THE AREA 1
0.2%
Tarmac road 2
0.3%
Tchembele zandonda za chilendo 1
0.2%
The comming in of electricity 1
0.2%
Thives in the area stilling farmers crops while in the field 1
0.2%
Tobacco Sales 1
0.2%
Two new boreholes 1
0.2%
Under five Clinic 1
0.2%
Unfair distribution of free or inkind foods 1
0.2%
Unreliable rainfall 1
0.2%
Water 1
0.2%
Water Problem 1
0.2%
Water and electricity 1
0.2%
Water kiosks 1
0.2%
Water too expensive 1
0.2%
Wold relief 1
0.2%
addition of communal stand pipe 1
0.2%
boreholes 1
0.2%
chinamwali 1
0.2%
coming of grid of electricity 1
0.2%
construction of school blocks 1
0.2%
construction of new road 1
0.2%
construction of school block 1
0.2%
construction of the road to nkhwisa 1
0.2%
constructions computer room for the school 1
0.2%
crop and pest deases 1
0.2%
crop and pest diseases 3
0.5%
crop disease 1
0.2%
crop diseases 1
0.2%
crop failure 2
0.3%
crop peasts 1
0.2%
crop pest and diseases 1
0.2%
crop pests and deseases 1
0.2%
crop pests and diseases 1
0.2%
crops Diseases 1
0.2%
crops diseases 1
0.2%
disease 1
0.2%
drop down of price of commodities 1
0.2%
drought 1
0.2%
earthquake 1
0.2%
electricity powerlines 1
0.2%
expensive of agriculture inputs and it's pricing of their commodities is very low 1
0.2%
farming 1
0.2%
fertilizer subsidy 1
0.2%
flooding 1
0.2%
floods 11
1.7%
grought 1
0.2%
heavy rains 1
0.2%
heavy wind that blows some household roof 1
0.2%
heavy winds 1
0.2%
high soya harvested 1
0.2%
high price of farm inputs 1
0.2%
high price of food items at the market 1
0.2%
high price of goods 1
0.2%
high prices of agricultural inputs 1
0.2%
hospital shelter 1
0.2%
human disease 2
0.3%
human diseases 1
0.2%
iiregular rains 1
0.2%
in adquate rains 1
0.2%
lack of employment opportunity 1
0.2%
lack of fertilizer 1
0.2%
lack of good roads 1
0.2%
livestock diseases 2
0.3%
low prices of crops on market 1
0.2%
low prices of Agriculture produces 1
0.2%
low prices of produce 2
0.3%
low prices of selling Agricultural products 1
0.2%
low yields 1
0.2%
masaf 4 1
0.2%
masaff employment opportunities 1
0.2%
new employment opportunities 2
0.3%
new road 1
0.2%
none 2
0.3%
over flooding 1
0.2%
over population 1
0.2%
pest 2
0.3%
pests 3
0.5%
political demostrations 1
0.2%
poor markets 1
0.2%
price fluctuation 1
0.2%
price fluctuations 1
0.2%
price influations 1
0.2%
price of Nandolo going up 1
0.2%
prostitutions 1
0.2%
rainstorm 1
0.2%
road 1
0.2%
school block 1
0.2%
school building 1
0.2%
shortage fertilizer 1
0.2%
shortage of Coupon 1
0.2%
stop children marriage 1
0.2%
strong wind 1
0.2%
turn back children to school 1
0.2%
unemployment 1
0.2%
weeding 1
0.2%
weevals 1
0.2%
winds 1
0.2%
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.
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